Displaying 7 of 37 results for "Peter Sloep" clear search
To tackle the scientific challenges proposed by landscape dynamics and cooperation processes, I have developed a research methodology based on field work and companion modelling (ComMod) combined with the formalisation of the observed processes and agents based models.
This approach offers the possibility to understand : spatial, social, cultural and / or economic conditions that take place on territories, and to provide prospective scenarios.
These methods have been applied in various contexts: steep slope vineyards landscapes (2011), water resource management cooperation (2015), vegetation cover in dry climate (2017). The established research networks are still active through sustained collaborations and activities.
My technical expertise grew and evolved through investment in several workgroups: MAPS Team (Modelling Applied to Space Phenomena), OSGeo (president of the OSGeo’s French chapter between 2013 and 2016, member of the OSGeo-international chapter since 2015), various initiatives around modelling, exploration and sensibility analysis of spatial patterns behaviours, and more generally in Free Software communities.
I am interested in the socio-environmental conditions for the emergence of cooperation and mutual aid in social systems and mainly with regard to renewable resources. I consider in this context that Commons are a spatial manifestation of mutual aid.
From a technical point of view, I am very interested in the questions of model exploration (HPC), which led me to integrate the OpenMole community and to contribute to discussions about heuristic exploration.
After being the economic development officer for the Little/Salmon Carmacks First Nation, Tim used all his spare time trying to determine a practical understanding of the events he witnessed. This led him to complexity, specifically human emergent behaviour and the evolutionary prerequisites present in human society. These prerequisites predicted many of the apparently immutable ‘modern problems’ in society. First, he tried disseminating the knowledge in popular book form, but that failed – three times. He decided to obtain PhD to make his ‘voice’ louder. He chose sociology, poorly as it turns out as he was told his research had ‘no academic value whatsoever’. After being forced out of University, he taught himself agent-based modelling to demonstrate his ideas and published his first peer-reviewed paper without affiliation while working as a warehouse labourer. Subsequently, he managed to interest Steve Keen in his ideas and his second attempt at a PhD succeeded. His most recent work involves understanding the basic forces generated by trade in a complex system. He is most interested in how the empirically present evolutionary prerequisites impact market patterns.
Economics, society, complexity, systems, ecosystem, thermodynamics, agent-based modelling, emergent behaviour, evolution.
Dr. Chairi Kiourt is a research associate with the ATHENA - Research and Innovation Centre in Information, Communication and Knowledge Technologies - Xanthi’s Division, multimedia department since 2014. Also, as of December 2017, heis PostDoctoral researcher with the Hellenic Open University, School of Science and Technology, and as of 2018, visiting Lecturer at the Department of Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Greece.
In 2003, he received his BSc degree in Electrical Engineering from the Electrical Engineering Department of the Eastern Macedonia and Thrace Institute of Technology, Greece. He also received an M.Sc. in System Engineering and Management in the specialty area: A. Information and Communication Systems Management from the Democritus University of Thrace, Greece. In 2017, received his PhD in Artificial Intelligence and Software Engineering from the Hellenic Open University. He has participated in several national and European research programs and co- authored to the writing of several scientific publications in international peer-reviewed journals and conferences with judges in the fields of collective artificial intelligence, multi-agent systems, reinforcement learning agents, virtual worlds, virtual museums and gamification.
Game playing multi-agent systems, reinforcement learning, colelctive artificial intelligence, distributed computing systems, virtual worlds, gamification
Mario Ureta holds a BSc in Economics from Birkbeck, University of London, a Graduate Diploma in Data Science from the London School of Economics, and an MSc in Data Science and Analytics from Brunel University London. He is currently a PhD student in Computing Science at Birkbeck, University of London. His research focuses on the economic study of individual preferences and decision-making, and on the use of agent-based models as a bridge between economic theory and computational experimentation. Through economic simulation, his work examines how heterogeneous preferences, social interaction, and firm behaviour jointly shape aggregate market outcomes, including non-linear dynamics and tipping points.
My research interests centre on the study of individual preferences in economics and on understanding how preferences evolve through interaction, learning, and social context. I am particularly interested in how seemingly weak or latent preferences—such as attitudes toward environmental attributes, prices, or social norms—can become amplified through feedback mechanisms and generate non-linear aggregate outcomes. A core methodological focus of my work is the use of agent-based modelling and economic simulation as a bridge between economic theory and experimentation. By treating agent-based models as computational laboratories, I explore how heterogeneous preferences, habit formation, peer influence, and firm behaviour interact dynamically, allowing theoretical mechanisms to be tested, stress-tested, and compared under controlled but flexible conditions that are difficult to achieve using purely analytical or empirical approaches.
He is a member of IEEE, a computer scientist, an Information Technologist, and a Research Lab Head at the Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda. My research broadly integrates and focuses on developing principled computationally and statistically efficient models and algorithms for various machine learning problems in Smart Agriculture, Ecological Informatics, Computer Vision, Applied AI, Cybersecurity and Privacy, and Smart Cities. I attained a Bachelor in Information Technology at the Faculty of Science & Computing, Ndejje University, Kampala, Uganda; a Master in Information Technology Engineering (Computer and Communication Networks); and PhD in Computer Science Universiti Brunei Darussalam, Brunei. He has received additional training from, among others, the National Institutes of Health, US Department of Health and Human Services, and the Bloomberg School of Public Health, USA. Hundreds of scholarly publications, including those in prestigious peer-reviewed journal articles, numerous IEEE International, non-IEEE Conference proceedings, book chapters, and books have been published. Reviewer/editorial support of over twelve (Scopus, Compendex (Elsevier Engineering Index), and WoS International Journals, including Expert Systems With Applications, Scientific Reports and Computers and Electronics in Agriculture. I served in several capacities, including being departmental support for Mathematics for Data Science, Advanced Topics in Computing, and Advanced Algorithms. Prior to this, I served as a community data officer at Pace-Uganda, a research associate at TechnoServe, a research assistant at PSI-Uganda, a research lead at the Socio-economic Data Centre (SEDC-Uganda) and ag. managing director at Asmaah Charity Organisation.
Computer Vision, Artificial Intelligence, Security and Privacy, Smart Agriculture / Digital Agriculture, Health Computing, Digital Image Processing,
Social Networks Analysis, Sustainable Computing, Ecological Informatics, Smart Computing
Flaminio Squazzoni is Full Professor of Sociology at the Department of Social and Political Sciences of the University of Milan and director of BEHAVE. He teaches “Sociology” to undergraduate students, “Behavioural Sociology” to master students and “Behavioural Game Theory” to PhD students. Untill November 2018, he has been Associate Professor of Economic Sociology at the Department of Economics and Management of the University of Brescia, where he led the GECS-Research Group on Experimental and Computational Sociology.
He is editor of JASSS-Journal of Artificial Societies and Social Simulation, co-editor of Sociologica -International Journal for Sociological Debate and member of the editorial boards of Research Integrity and Peer Review and Sistemi Intelligenti. He is advisory editor of the Wiley Series in Computational and Quantitative Social Science and the Springer Series in Computational Social Science and member of the advisory board of ING’s ThinkForward Initiative. He is former President of the European Social Simulation Association (Sept 2012/Sept 2016, since 2010 member of the Management Committee) and former Director of the NASP ESLS PhD Programme in Economic Sociology and Labour Studies (2015-2016).
His fields of research are behavioural sociology, economic sociology and sociology of science, with a particular interest on the effect of social norms and institutions on cooperation in decentralised, large-scale social systems. His research has a methodological focus, which lies in the intersection of experimental (lab) and computational (agent-based modelling) research.
I am an Associate Professor of Industrial Engineering with over two decades of experience in teaching, research, and supervision in data-driven decision making, operations research, and computational modeling. My research integrates Multi-Criteria Decision Analysis (MCDA), Agent-Based Modeling (ABM), and Reinforcement Learning (RL) to support strategic decision systems in sustainability, investment, and industrial operations. My recent work explores human-centric and multi-actor systems, leveraging simulation-based optimization and AI-driven analytics to enhance resilience, efficiency, and sustainability in complex socio-technical environments. I have published extensively in international journals, reviewed over 75 manuscripts, and am an active member of INFORMS and the System Dynamics Society. My long-term goal is to bridge industrial systems modeling with intelligent decision support, aligning academic research with real-world sustainability and innovation challenges.
🔹 Experience
Associate Professor — Industrial Engineering, University of Engineering and Technology, Taxila (2018 – Present)• Teach graduate and undergraduate courses in Operations Research, Data Mining, Advanced Statistics, System Simulation, and Soft Computing.• Conduct funded research in agent-based and reinforcement learning models for sustainable and data-driven decision systems.• Supervise doctoral students in decision analytics, multi-agent modeling, and MCDM applications.• Reviewer for international journals including Neural Computing and Applications, the Journal of Cleaner Production, Annals of Operations Research, Environment, Development and Sustainability, Energy for Sustainable Development, Scientific Reports, IEEE Access, Cleaner Energy Systems, Utilities Policy, and Sustainable Futures
🔹 Research Interests•
Data-Driven Decision Making• Agent-Based Modeling (ABM)• Reinforcement Learning (RL)• Multi-Criteria Decision Analysis (MCDA / MAMCA)• Sustainable Supply Chains• System Dynamics; Simulation• E-Health and Humanitarian Systems
🔹 Selected Achievements•
30+ peer-reviewed publications; ~360+ citations• Reviewer for 75+ international journal papers• Completed Coursera Specializations in Machine Learning, Deep Learning, and Reinforcement Learning• 20+ years of experience integrating data science with sustainability modeling
Data-Driven Decision Making | Agent-Based & Reinforcement Learning Models | Multi-Criteria Decision Analysis | Sustainable Systems | Operations Research | Netlogo | R
Displaying 7 of 37 results for "Peter Sloep" clear search